4 papers
Boundary-aware Prototype-driven Adversarial Alignment for Cross-Corpus EEG Emotion Recognition
Guangli Li, Canbiao Wu, Na Tian +2
Electroencephalography (EEG)-based emotion recognition suffers from severe performance degradation when models are transferred across heterogeneous datasets due to physiological va…
Learning Domain- and Class-Disentangled Prototypes for Domain-Generalized EEG Emotion Recognition
Guangli Li, Canbiao Wu, Zhehao Zhou +3
Electroencephalography (EEG)-based emotion recognition plays a critical role in affective Brain-Computer Interfaces (aBCIs), yet its practical deployment remains limited by inter-s…
PL-DCP: A Pairwise Learning framework with Domain and Class Prototypes for EEG emotion recognition under unseen target conditions
Guangli Li, Canbiao Wu, Zhehao Zhou +4
Electroencephalogram (EEG) signals serve as a powerful tool in affective Brain-Computer Interfaces (aBCIs) and play a crucial role in affective computing. In recent years, the intr…
Unsupervised Pairwise Learning Optimization Framework for Cross-Corpus EEG-Based Emotion Recognition Based on Prototype Representation
Guangli Li, Canbiao Wu, Zhen Liang
Affective computing is a rapidly developing interdisciplinary research direction in the field of brain-computer interface. In recent years, the introduction of deep learning techno…